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Team 4

Members

  • Julia Ariadna Blanco Arnaus
  • Marcos Muñoz González
  • Abel García Romera
  • Hicham El Muhandiz Aarab

Project description

In this project we explore the task of video sequence analysis, more specifically video surveillance. Initially, we use statistical models to estimate background information of video sequences and track the cars on them. We also leverage deep learning techniques which can be used to detect objects in specific regions of interest in a video. Moreover, optical flow estimations and tracking algorithms are used to track the different objects. Finally, we use several useful metrics for the task of tracking. Those techniques are suitable for surveillance, robotics, or any other field where video analysis is important.

The dataset used is CVPR 2020 AI City Challenge - Track1. Which can be found on: https://www.aicitychallenge.org/2023-data-and-evaluation/

Final presentation slides

https://docs.google.com/presentation/d/1nIyObPnBSzQkoAfdtGu5g_cRmdkPdrvoEXVzozqP84g/edit?usp=sharing

Final report

https://www.overleaf.com/read/fnygdrftdjyw

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